Common Types
Use these guides to understand the shared resource, memory, and array abstractions used by NVIDIA cuVS APIs.
- Array Types: choose between dense arrays and sparse arrays for NVIDIA cuVS APIs.
- Dense Arrays: pass dense vectors, matrices, and outputs into NVIDIA cuVS APIs across supported languages.
- Memory Management: configure RMM device, pool, pinned host, host, and managed memory resources for NVIDIA cuVS workflows.
- Multi-GPU: initialize multi-GPU resources and understand RAFT/NCCL communication setup.
- Resources: reuse CUDA streams, library handles, stream pools, and workspace resources across NVIDIA cuVS calls.
- Sparse Arrays: use CSR and COO sparse matrix views with NVIDIA cuVS C++ APIs that accept sparse inputs.